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共 1871 条记录，以下是1-10 订阅

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4th international conference on intelligent systems and pattern recognition, ispr 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on intelligent systems and pattern recognition, ispr 2024

ISBN: (纸本)9783031821493

the proceedings contain 77 papers. the special focus in this conference is on intelligent systems and pattern recognition. the topics include: Tunisian Sign Language recognition and Translation Using Deep Learning;Beyond Spatial: A Wavelet Fusion-Based Deep Learning CAD for Skin Cancer Diagnosis;integrating Machine Learning and Deep Learning Techniques for Enhanced Historical Script Classification;efficiency Meets Resilience: Accelerating Object Detection in Embedded Environments through Compressive Sensing;PMoET: Going Wider than Deeper Using the Parallel Mixture of Experts Transformer for 3D Hand Gesture recognition;Enhancing Forest Fire Classification with Feature Selection and Machine Learning Based on PRISMA Hyperspectral Data;semantic Segmentation of Unmanned Aerial Vehicle Remote Sensing Images Using SegFormer;handcrafted and Deep Features for Synthetic Data Generation in Offline Handwritten Signature Verification;refining U-Net Architecture through Genetic Algorithms for Improved Skin Lesion Image Segmentation;An RNN-LSTM Approach for Algerian Accent Identification;ensemble Methods for Predicting Cyanobacteria’s Potential Toxicity in Water Dams;cross-Organ Investigation of Tumor Histological Features Similarities Using Transfer Learning: A Case Study on Breast and Colorectal Tumors;behavior-Based Insider threat Detection Using a Deep Neural Network;holistic Ontology Alignment Using Ontologies Embeddings;learning Different Separations in Branch and Cut: A Survey;Cancer Classification in Breast Imaging via Enhanced CNN Deep Learning Architecture;X-Ray Insights: A Siamese with CNN and Spatial Attention Network for Innovative Person Identification;hybrid Wiener Filter and Sharpening Filter for Image De-blurring;feature Extraction and Dimensionality Reduction to Evaluate Decision Tree Ensembles for Diabetic Retinopathy Detection;artificial Intelligence-Based on Automatic Detection of Diabetic Eye Diseases : A Systematic Review;automated Breast Cancer Detection: A

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4th international conference on intelligent systems and pattern recognition, ispr 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on intelligent systems and pattern recognition, ispr 2024

ISBN: (纸本)9783031821554

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4th international conference on intelligent systems and pattern recognition, ispr 2024

4th International Conference on Intelligent Systems and Patt...

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4th international conference on intelligent systems and pattern recognition, ispr 2024

ISBN: (纸本)9783031821523

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4th international conference on pattern Analysis and intelligent systems, PAIS 2022 - Proceedings

4th International Conference on Pattern Analysis and Intelli...

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4th international conference on pattern Analysis and intelligent systems, PAIS 2022

ISBN: (纸本)9781665461610

the proceedings contain 57 papers. the topics discussed include: a deep learning-based system for detection at-risk students;an explainable self-labeling grey-box model;development of a biometric authentication platform using voice recognition;binary Archimedes optimization algorithm based feature selection for regression problem;semantic segmentation of breast cancer histopathology images using deep learning;a biased random-key genetic algorithm for extractive single-document summarization;a virtual clustering for data dissemination in vehicular fog computing;a novel method of requirements analysis for big data projects;combination of closed-set and open-set biometric identification;a formal integrated approach for cyber physical systems;and testing cyber-physical production system: test methods categorization and dataset.

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Proceedings - 2022 4th international conference on pattern recognition and intelligent systems, PRIS 2022

Proceedings - 2022 4th International Conference on Pattern R...

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4th international conference on pattern recognition and intelligent systems, PRIS 2022

ISBN: (纸本)9781450396080

the proceedings contain 17 papers. the topics discussed include: image data augmentation method based on style transfer;FPGA hardware implementation of Q-learning algorithm with low resource consumption;a machine-learning pipeline for semantic-aware and contexts-rich video description method;multi-scale and kernel-predicting convolutional networks for Monte Carlo denoising;single image dehazing algorithm based on generative adversarial network;biparted hyperboloid and sphere intersection algorithm;optimal sensor deployment in complex 3D terrain surface;weakly supervised road garbage quantification system based on WCCA;online detection of character and 3D surface defect in steel rail production;a credit scoring ensemble framework using Adaboost and multi-layer ensemble classification;and an LSTM-based method for recognition and prediction of aircraft formation.

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Leveraging Knowledge Graphs for Paper Recommendation systems 4th

Leveraging Knowledge Graphs for Paper Recommendation Systems

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Mataoui, M'hamed Bahloul, Haithem Ziane, Allaeddine Ecole Mil Polytech Dept Comp Sci Algiers Algeria

ISBN: (纸本)9783031821493;9783031821509

With the exponential growth of academic publications, researchers face significant challenges in efficiently discovering relevant resources for their research and development tasks. In response, recommender systems have emerged as a valuable tool, demonstrating success in various domains. In this work, we present a comprehensive architecture for an academic recommendation system based on knowledge graphs. the proposed architecture encompasses the entire process, starting from data collection, named entity recognition, knowledge graph construction to the generation of the recommendations. Our knowledge graph construction approach employs fine-tuned SciBERT, trained on SciREX, to extract key information, such as, methods and datasets referenced in academic publications. Additionally, we integrated CSO Ontology to extract topics related to the processed publications, to enhance the recommendation process. Furthermore, we propose a novel method that utilizes embeddings and similarity measures to generate personalized recommendations. To evaluate the developed prototype, we collaborated with computer science experts according to a proposed rating scale. the preliminary evaluation results confirm the system's ability to effectively recommend relevant publications.

关键词： Knowledge Graphs Academic Recommendation SciBERT SciREX CSO Ontology

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Handcrafted and Deep Features for Synthetic Data Generation in Offline Handwritten Signature Verification 4th

Handcrafted and Deep Features for Synthetic Data Generation ...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Arab, Naouel Nemmour, Hassiba Bouibed, Mohamed Lamine Chibani, Youcef Univ Sci & Technol Houari Boumediene USTHB Lab Ingn Syst Intelligents & Commun LISIC Fac Elect Engn Algiers Algeria

ISBN: (纸本)9783031821554;9783031821561

One of the major limitations which obstruct the development of an efficient offline signature verification system is the lack of genuine signatures required to perform a reliable training stage. To deal with this issue, data augmentation techniques are employed to add synthetic genuine signatures. Presently, the signature verification system is developed by applying an algorithm for synthetic features generation. We evaluate the effectiveness of this feature generator with two different signature descriptors. the first descriptor is the Local Directional Strength patterns while the second descriptor is based on the SigNet deep features. the verification phase is carried out with an SVM classifier. Experiments are performed on CEDAR and MCYT-75 datasets according to the writer-dependent verification approach. the inclusion of synthetic features considerably enhances the system performance, yielding a gain of 17% when the verification system employs only one real signature. Compared to handcrafted features, the SigNet provide more effective synthetic features with both datasets.

关键词： Artificial Immune System Handwritten Signature Verification Local Directional Strength pattern SigNet features Synthetic feature generation

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Leveraging DQN-Based Recommender systems for E-Commerce in Smart Cities 4th

Leveraging DQN-Based Recommender Systems for E-Commerce in S...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Abakarim, Sana Qassimi, Sara Rakrak, Said Cadi Ayyad Univ Fac Sci & Tech L2IS Lab Marrakech Morocco

ISBN: (纸本)9783031821523;9783031821530

In the age of digital urban transformation, smart cities are emerging as ecosystems where technology, infrastructure and data converge to improve quality of life, sustainability and economic prosperity. In this context, e-commerce plays a central role, providing platforms for businesses to thrive by enabling seamless transactions, personalised shopping experiences and greater market reach. However, the dynamic and evolving nature of user preferences presents a significant challenge, requiring more adaptive and smart recommendation systems. this paper presents an approach by integrating Deep Q-Network (DQN), a reinforcement learning technique, into recommendation systems for e-commerce in smart cities. By comparing the proposed DQN model based recommender system with traditional models such as MLP, DeepFM, LSTM and CNN using metrics such as MSE, RMSE and NDCG@5, we demonstrate its superior performance in predicting user preferences and dynamically adapting to changes in user behaviour. the results highlight the potential of DQN models to revolutionise e-commerce recommender systems, delivering more personalised and adaptive user experiences in the interconnected environments of smart cities.

关键词： Deep Q-Network Recommender systems Reinforcement Learning Smart Cities E-Commerce Machine Learning Deep Reinforcement Learning

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Advancing Systematic Literature Reviews Methodology through Topic Modeling 4th

Advancing Systematic Literature Reviews Methodology Through ...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Mekaoui, Salma Chaker, Ilham Zarghili, Arsalane Nikolov, Nikola S. Univ Limerick Dept Comp Sci & Informat Syst Limerick V94 T9PX Ireland Univ Sidi Mohamed Ben Abdellah Fac Sci & Technol Lab Intelligent Syst & Applicat Fes Morocco

ISBN: (纸本)9783031821493;9783031821509

the benefits of conducting a systematic review (SR) within a research project are well recognised. Nonetheless, nowadays an SR demands significant time and effort as it typically requires manually sifting through a large corpus of papers. In this work, we propose an application that simplifies the SR process for researchers by performing topic modeling. Our approach involves more than just conducting topic modeling;it entails selecting the optimal method tailored to our system's needs. We explore two widely recognized methods in topic modeling, namely Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF), alongside two prominent libraries, Scikit-learn and Gensim, which provide implementations for these methods. the evaluation of these methods and libraries is done with the help of the cosine similarity metric. Our findings indicate that, for our research context, LDA implemented in Scikit-learn stands out as the most effective method for topic modeling. Additionally, our study suggests that employing 10 topics, along with stemming and lemmatization, yields better results. Our findings culminate in the development of an application to facilitate SRs for researchers.

关键词： Topic modeling LDA NMF Systematic review

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Boosting CRM Chatbot Solutions with Flash Attention and Probabilistic Inference 4th

Boosting CRM Chatbot Solutions with Flash Attention and Prob...

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4th international conference on intelligent systems and pattern recognition-ispr

作者： Gunay, Ahmet Can Ozara, Muhammet Furkan Celik, Ahmet Erkan Akbulut, Akhan Next4biz R&D Ctr Pakpen Plaza 40-4 TR-34734 Istanbul Turkiye Istanbul Kultur Univ Dept Comp Engn TR-34536 Istanbul Turkiye

ISBN: (纸本)9783031821493;9783031821509

In an effort to deliver exceptional customer service, organizations are increasingly recognising the critical role that advanced language models (LLMs) play in the integration of CRM systems. this article explores the forefront of chatbot technology, with a particular focus on the essential function they play in contemporary consumer relationship management. the ability of chatbots to provide personalized and contextually pertinent responses to customer inquiries has been significantly enhanced by the rapid development of LLMs, specifically in the areas of sentiment, intent, and context comprehension. Organizations have the opportunity to enhance customer contentment and optimize operations by leveraging the capabilities of these advanced AI systems. In addition, offline capabilities guarantee continuous support, thereby enhancing customer confidence and loyalty in a time when connectivity fluctuations continue to be a challenge. the present study introduces an innovative offline chatbot system that aims to overcome the limitations of traditional cloud-based counterparts. By efficiently integrating data from various sources, such as project documentation and social media, this chatbot is capable of operating independently and delivering assistance to users, even in locations with sporadic internet connectivity. the experimental outcomes illustrate that our newly developed chatbot model outperforms established benchmarks, as evidenced by its 4.1-second inference time, 90.2-point BLEU score, and 9.7-point WER score. these metrics underscore the model's effectiveness, precision, and timeliness in handling user inquiries and producing responses of exceptional quality. the experiments we conduct are designed to validate the effectiveness of our model in improving customer service experiences within CRM systems through comprehensive performance testing.

关键词： Natural Language Processing NLP Chatbot Flash Attention Probabilistic Inference Data ingestion

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